Category: Papers

Warnings and Caveats in Brain Controllability

In this work we challenge the main conclusions of Gu et al work (Controllability of structural brain networks. Nature communications 6, 8414, doi:10.1038/ncomms9414, 2015) on brain controllability. Using the same methods and analyses on four datasets we find that the minimum set of nodes to control brain networks is always larger than one. We also find that the relationships between the average/modal controllability and weighted degrees also hold for randomized data and the there are not specific roles played by Resting State Networks in controlling the brain. In conclusion, we show that there is no evidence that topology plays specific and unique roles in the controllability of brain networks. Accordingly, Gu et al. interpretation of their results, in particular in terms of translational applications (e.g. using single node controllability properties to define target region(s) for neurostimulation) should be revisited. Though theoretically intriguing, our understanding of the relationship between controllability and structural brain network remains elusive.

Source: arxiv.org

Evolutionary games on scale-free multiplex networks

Evolutionary games on structured populations have been studied extensively in recent years. In reality, social interactions take place in different domains, which naturally requires a multiplex description. The impact of the multiplex nature of human interactions on the evolution of cooperation has recently attracted a lot of attention, however, the fundamental mechanisms at play are still not well understood. Here, we show that the interplay between the structural organization of the multiplex and the assumptions about the dynamical coupling between the layers leads to very different outcomes. We show that the organization of the multiplex can enable mutual spatial selection, which refers to the formation of overlapping clusters of cooperators in different layers that can survive in social dilemmas. Furthermore, heterogeneity and degree correlations lead to topological enslavement, which means that the hubs dominate the game dynamics inducing payoff irrelevance. Our findings reveal the fundamental mechanisms at play and provide a new perspective for understanding the evolution of cooperation on realistic structured populations.

 

Evolutionary games on scale-free multiplex networks
Kaj-Kolja Kleineberg

Source: arxiv.org

On the records

World record setting has long attracted public interest and scientific investigation. Extremal records summarize the limits of the space explored by a process, and the historical progression of a record sheds light on the underlying dynamics of the process. Existing analyses of prediction, statistical properties, and ultimate limits of record progressions have focused on particular domains. However, a broad perspective on how record progressions vary across different spheres of activity needs further development. Here we employ cross-cutting metrics to compare records across a variety of domains, including sports, games, biological evolution, and technological development. We find that these domains exhibit characteristic statistical signatures in terms of rates of improvement, “burstiness” of record-breaking time series, and the acceleration of the record breaking process. Specifically, sports and games exhibit the slowest rate of improvement and a wide range of rates of “burstiness.” Technology improves at a much faster rate and, unlike other domains, tends to show acceleration in records. Many biological and technological processes are characterized by constant rates of improvement, showing less burstiness than sports and games. It is important to understand how these statistical properties of record progression emerge from the underlying dynamics. Towards this end, we conduct a detailed analysis of a particular record-setting event: elite marathon running. In this domain, we find that studying record-setting data alone can obscure many of the structural properties of the underlying process. The marathon study also illustrates how some of the standard statistical assumptions underlying record progression models may be inappropriate or commonly violated in real-world datasets.

 

On the records

Andrew Berdahl, Uttam Bhat, Vanessa Ferdinand, Joshua Garland, Keyan Ghazi-Zahedi, Justin Grana, Joshua A. Grochow, Elizabeth Hobson, Yoav Kallus, Christopher P. Kempes, Artemy Kolchinsky, Daniel B. Larremore, Eric Libby, Eleanor A. Power, Brendan D. Tracey (Santa Fe Institute Postdocs)

Source: arxiv.org

Machine learning: the power and promise of computers that learn by example

What is the potential of machine learning over the next 5-10 years? And how can we develop this technology in a way that benefits everyone? 

The Royal Society’s machine learning project has been investigating these questions, and has today launched a report setting out the action needed to maintain the UK’s role in advancing this technology while ensuring careful stewardship of its development.

Machine learning is a form of artificial intelligence that allows computer systems to learn from examples, data, and experience. Through enabling computers to perform specific tasks intelligently, machine learning systems can carry out complex processes by learning from data, rather than following pre-programmed rules.

Source: royalsociety.org

People on the move

Science helps us think more clearly about migration, in part by showing its deep roots. Researchers wielding powerful new methods have discovered ancient, hidden migrations that shaped today’s populations. Go back far enough and almost all of us are immigrants, despite cherished stories of ethnic and national origins. Science can also aid the 21 million migrants today who are refugees from violence or famine, according to the United Nations. They need food, medicine, and shelter now, but in the long run it is their mental health that will be key to building new lives, as shown by a case study of the long-persecuted Yezidis. The success of these and other immigrants depends in part on whether new countries spurn or welcome them, and research is starting to show how to manage our long-standing biases against outsiders.

 

People on the move
Elizabeth Culotta

Science 19 May 2017:
Vol. 356, Issue 6339, pp. 676-677
DOI: 10.1126/science.356.6339.676

Source: science.sciencemag.org